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Return the sum using add(a, b).
def add(a, b): return a + b
code_add
train_seen
Instruction: Return the sum using add(a, b). Answer: def add(a, b): return a + b <END>
User: Please call me Evan. User: What name should you use?
Evan.
context_name
train_seen
Instruction: User: Please call me Evan. User: What name should you use? Answer: Evan. <END>
Make a function called add that uses plus.
def add(a, b): return a + b
code_add
train_regression
Instruction: Make a function called add that uses plus. Answer: def add(a, b): return a + b <END>
Give a tiny explanation of return in Python.
A return statement sends a value back from a function.
return_statement
train_seen
Instruction: Give a tiny explanation of return in Python. Answer: A return statement sends a value back from a function. <END>
Write the SUBTRACT function.
def subtract(a, b): return a - b
code_subtract
train_seen
Instruction: Write the SUBTRACT function. Answer: def subtract(a, b): return a - b <END>
Sentiment of this text: I love this tool.
positive
sentiment_positive
train_seen
Instruction: Sentiment of this text: I love this tool. Answer: positive <END>
User: My name is Evan. User: What is my name?
Evan.
context_name
train_seen
Instruction: User: My name is Evan. User: What is my name? Answer: Evan. <END>
Write a Python subtract function using the - operator.
def subtract(a, b): return a - b
code_subtract
train_seen
Instruction: Write a Python subtract function using the - operator. Answer: def subtract(a, b): return a - b <END>
What food did Evan eat today?
I don't know from the given information.
idk_food_today
train_seen
Instruction: What food did Evan eat today? Answer: I don't know from the given information. <END>
Give a tiny explanation of return in Python.
A return statement sends a value back from a function.
return_statement
train_seen
Instruction: Give a tiny explanation of return in Python. Answer: A return statement sends a value back from a function. <END>
If you lack logs and files, what should you ask for?
Ask for the missing evidence.
evidence_missing
train_seen
Instruction: If you lack logs and files, what should you ask for? Answer: Ask for the missing evidence. <END>
Give me subtract(a, b) for subtraction.
def subtract(a, b): return a - b
code_subtract
train_seen
Instruction: Give me subtract(a, b) for subtraction. Answer: def subtract(a, b): return a - b <END>
Rewrite professionally: I can't make it.
I am unable to attend.
rewrite_professional_attend
train_seen
Instruction: Rewrite professionally: I can't make it. Answer: I am unable to attend. <END>
What comes before patching files?
Inspect the current files first.
inspect_first
train_seen
Instruction: What comes before patching files? Answer: Inspect the current files first. <END>
Write the SUBTRACT function.
def subtract(a, b): return a - b
code_subtract
train_seen
Instruction: Write the SUBTRACT function. Answer: def subtract(a, b): return a - b <END>
Make a function called add that uses plus.
def add(a, b): return a + b
code_add
train_regression
Instruction: Make a function called add that uses plus. Answer: def add(a, b): return a + b <END>
Return a + b from a function named add.
def add(a, b): return a + b
code_add
train_seen
Instruction: Return a + b from a function named add. Answer: def add(a, b): return a + b <END>
What is the point of tests?
Tests show whether the code still behaves as expected.
tests_matter
train_seen
Instruction: What is the point of tests? Answer: Tests show whether the code still behaves as expected. <END>
If you do not have enough current evidence, what is the right move?
Ask for the missing evidence.
evidence_missing
train_seen
Instruction: If you do not have enough current evidence, what is the right move? Answer: Ask for the missing evidence. <END>
What should happen before guessing a patch?
Ask for the missing evidence.
evidence_missing
train_seen
Instruction: What should happen before guessing a patch? Answer: Ask for the missing evidence. <END>
Sentiment of this text: This is broken.
negative
sentiment_negative
train_seen
Instruction: Sentiment of this text: This is broken. Answer: negative <END>
User: Call me Evan. User: What should you call me?
Evan.
context_name
train_regression
Instruction: User: Call me Evan. User: What should you call me? Answer: Evan. <END>
Tell me what Evan ate today.
I don't know from the given information.
idk_food_today
train_seen
Instruction: Tell me what Evan ate today. Answer: I don't know from the given information. <END>
What should you do if the evidence is missing?
Ask for the missing evidence.
evidence_missing
train_seen
Instruction: What should you do if the evidence is missing? Answer: Ask for the missing evidence. <END>
If you cannot verify the project state, what is the right response?
Ask for the missing evidence.
evidence_missing
train_seen
Instruction: If you cannot verify the project state, what is the right response? Answer: Ask for the missing evidence. <END>
What comes before patching files?
Inspect the current files first.
inspect_first
train_seen
Instruction: What comes before patching files? Answer: Inspect the current files first. <END>
Context: name: Evan. Question: Which name was given?
Evan.
context_name
train_seen
Instruction: Context: name: Evan. Question: Which name was given? Answer: Evan. <END>
Return the product using multiply(a, b).
def multiply(a, b): return a * b
code_multiply
train_seen
Instruction: Return the product using multiply(a, b). Answer: def multiply(a, b): return a * b <END>
On a clear day, what color is the sky?
Blue.
sky_color
train_seen
Instruction: On a clear day, what color is the sky? Answer: Blue. <END>
Return a + b from a function named add.
def add(a, b): return a + b
code_add
train_seen
Instruction: Return a + b from a function named add. Answer: def add(a, b): return a + b <END>
Which film is my favorite?
I don't know from the given information.
idk_favorite_movie
train_regression
Instruction: Which film is my favorite? Answer: I don't know from the given information. <END>
Make a function called subtract that uses minus.
def subtract(a, b): return a - b
code_subtract
train_regression
Instruction: Make a function called subtract that uses minus. Answer: def subtract(a, b): return a - b <END>
Write a Python subtract function using the - operator.
def subtract(a, b): return a - b
code_subtract
train_seen
Instruction: Write a Python subtract function using the - operator. Answer: def subtract(a, b): return a - b <END>
What is the capital of France?
Paris.
capital_france
train_seen
Instruction: What is the capital of France? Answer: Paris. <END>
Make this professional: I can't make it.
I am unable to attend.
rewrite_professional_attend
train_seen
Instruction: Make this professional: I can't make it. Answer: I am unable to attend. <END>
Sentiment of this text: I love this tool.
positive
sentiment_positive
train_seen
Instruction: Sentiment of this text: I love this tool. Answer: positive <END>
What is the first move before touching project files?
Inspect the current files first.
inspect_first
train_seen
Instruction: What is the first move before touching project files? Answer: Inspect the current files first. <END>
Create subtract so it computes a minus b.
def subtract(a, b): return a - b
code_subtract
train_seen
Instruction: Create subtract so it computes a minus b. Answer: def subtract(a, b): return a - b <END>
Do you have enough information to name my favorite movie?
I don't know from the given information.
idk_favorite_movie
train_seen
Instruction: Do you have enough information to name my favorite movie? Answer: I don't know from the given information. <END>
Write the MULTIPLY function.
def multiply(a, b): return a * b
code_multiply
train_seen
Instruction: Write the MULTIPLY function. Answer: def multiply(a, b): return a * b <END>
Explain what a return statement does.
A return statement sends a value back from a function.
return_statement
train_seen
Instruction: Explain what a return statement does. Answer: A return statement sends a value back from a function. <END>
Yes or no: does a square have five sides? Explain.
No, because a square has exactly four sides.
no_square_five_sides
train_seen
Instruction: Yes or no: does a square have five sides? Explain. Answer: No, because a square has exactly four sides. <END>
What is my favorite movie?
I don't know from the given information.
idk_favorite_movie
train_seen
Instruction: What is my favorite movie? Answer: I don't know from the given information. <END>
Yes or no: can water become ice? Explain.
Yes, because water can become ice when it is cold enough.
yes_water_freeze
train_seen
Instruction: Yes or no: can water become ice? Explain. Answer: Yes, because water can become ice when it is cold enough. <END>
Create an add function that returns a plus b.
def add(a, b): return a + b
code_add
train_seen
Instruction: Create an add function that returns a plus b. Answer: def add(a, b): return a + b <END>
Make a Python function named divide that divides a by b.
def divide(a, b): return a / b
code_divide
train_seen
Instruction: Make a Python function named divide that divides a by b. Answer: def divide(a, b): return a / b <END>
Return the sum using add(a, b).
def add(a, b): return a + b
code_add
train_seen
Instruction: Return the sum using add(a, b). Answer: def add(a, b): return a + b <END>
Is a five-sided square possible? Give a reason.
No, because a square has exactly four sides.
no_square_five_sides
train_seen
Instruction: Is a five-sided square possible? Give a reason. Answer: No, because a square has exactly four sides. <END>
What movie do I like most?
I don't know from the given information.
idk_favorite_movie
train_seen
Instruction: What movie do I like most? Answer: I don't know from the given information. <END>
Return the difference using subtract(a, b).
def subtract(a, b): return a - b
code_subtract
train_seen
Instruction: Return the difference using subtract(a, b). Answer: def subtract(a, b): return a - b <END>
What should happen before touching code?
Inspect the current files first.
inspect_first
train_seen
Instruction: What should happen before touching code? Answer: Inspect the current files first. <END>
What is my favorite movie?
I don't know from the given information.
idk_favorite_movie
train_seen
Instruction: What is my favorite movie? Answer: I don't know from the given information. <END>
Write the ADD function.
def add(a, b): return a + b
code_add
train_seen
Instruction: Write the ADD function. Answer: def add(a, b): return a + b <END>
Before making file changes, what should you inspect?
Inspect the current files first.
inspect_first
train_seen
Instruction: Before making file changes, what should you inspect? Answer: Inspect the current files first. <END>
Classify this as code or prose: The cat sat down.
prose
classify_prose
train_seen
Instruction: Classify this as code or prose: The cat sat down. Answer: prose <END>
What should happen before guessing a patch?
Ask for the missing evidence.
evidence_missing
train_seen
Instruction: What should happen before guessing a patch? Answer: Ask for the missing evidence. <END>
What movie do I like most?
I don't know from the given information.
idk_favorite_movie
train_seen
Instruction: What movie do I like most? Answer: I don't know from the given information. <END>
Label the sentiment: This is broken.
negative
sentiment_negative
train_seen
Instruction: Label the sentiment: This is broken. Answer: negative <END>
Make a Python function named add that adds two numbers.
def add(a, b): return a + b
code_add
train_seen
Instruction: Make a Python function named add that adds two numbers. Answer: def add(a, b): return a + b <END>
What is the first move before touching project files?
Inspect the current files first.
inspect_first
train_seen
Instruction: What is the first move before touching project files? Answer: Inspect the current files first. <END>
Which film is my favorite?
I don't know from the given information.
idk_favorite_movie
train_regression
Instruction: Which film is my favorite? Answer: I don't know from the given information. <END>
What should you do before making a blind fix?
Ask for the missing evidence.
evidence_missing
train_regression
Instruction: What should you do before making a blind fix? Answer: Ask for the missing evidence. <END>
Return a - b from a function named subtract.
def subtract(a, b): return a - b
code_subtract
train_seen
Instruction: Return a - b from a function named subtract. Answer: def subtract(a, b): return a - b <END>
Context: name: Evan. Question: Which name was given?
Evan.
context_name
train_regression
Instruction: Context: name: Evan. Question: Which name was given? Answer: Evan. <END>
If you cannot verify the project state, what is the right response?
Ask for the missing evidence.
evidence_missing
train_seen
Instruction: If you cannot verify the project state, what is the right response? Answer: Ask for the missing evidence. <END>
Make a Python function named add that adds two numbers.
def add(a, b): return a + b
code_add
train_seen
Instruction: Make a Python function named add that adds two numbers. Answer: def add(a, b): return a + b <END>
Which film is my favorite?
I don't know from the given information.
idk_favorite_movie
train_regression
Instruction: Which film is my favorite? Answer: I don't know from the given information. <END>
Create multiply so it computes a times b.
def multiply(a, b): return a * b
code_multiply
train_seen
Instruction: Create multiply so it computes a times b. Answer: def multiply(a, b): return a * b <END>
What comes before patching files?
Inspect the current files first.
inspect_first
train_seen
Instruction: What comes before patching files? Answer: Inspect the current files first. <END>
Context: user name = Evan. Question: What name is stored?
Evan.
context_name
train_seen
Instruction: Context: user name = Evan. Question: What name is stored? Answer: Evan. <END>
Conversation: User: The name is Evan. User: What is the name?
Evan.
context_name
train_seen
Instruction: Conversation: User: The name is Evan. User: What is the name? Answer: Evan. <END>
Context: The user's name is Evan. Question: What is the user's name?
Evan.
context_name
train_seen
Instruction: Context: The user's name is Evan. Question: What is the user's name? Answer: Evan. <END>
Make a function called add that uses plus.
def add(a, b): return a + b
code_add
train_seen
Instruction: Make a function called add that uses plus. Answer: def add(a, b): return a + b <END>
If you cannot verify the project state, what is the right response?
Ask for the missing evidence.
evidence_missing
train_seen
Instruction: If you cannot verify the project state, what is the right response? Answer: Ask for the missing evidence. <END>
Which film is my favorite?
I don't know from the given information.
idk_favorite_movie
train_regression
Instruction: Which film is my favorite? Answer: I don't know from the given information. <END>
Make a Python function named add that adds two numbers.
def add(a, b): return a + b
code_add
train_seen
Instruction: Make a Python function named add that adds two numbers. Answer: def add(a, b): return a + b <END>
What should you do before making a blind fix?
Ask for the missing evidence.
evidence_missing
train_regression
Instruction: What should you do before making a blind fix? Answer: Ask for the missing evidence. <END>
In Python, what is return for?
A return statement sends a value back from a function.
return_statement
train_seen
Instruction: In Python, what is return for? Answer: A return statement sends a value back from a function. <END>
What is the first move before touching project files?
Inspect the current files first.
inspect_first
train_seen
Instruction: What is the first move before touching project files? Answer: Inspect the current files first. <END>
What is my favorite movie?
I don't know from the given information.
idk_favorite_movie
train_seen
Instruction: What is my favorite movie? Answer: I don't know from the given information. <END>
Write add(a, b).
def add(a, b): return a + b
code_add
train_seen
Instruction: Write add(a, b). Answer: def add(a, b): return a + b <END>
Which film is my favorite?
I don't know from the given information.
idk_favorite_movie
train_regression
Instruction: Which film is my favorite? Answer: I don't know from the given information. <END>
Context: The user's name is Evan. Question: What is the user's name?
Evan.
context_name
train_seen
Instruction: Context: The user's name is Evan. Question: What is the user's name? Answer: Evan. <END>
If the command output is missing, what should you ask for?
Ask for the missing evidence.
evidence_missing
train_seen
Instruction: If the command output is missing, what should you ask for? Answer: Ask for the missing evidence. <END>
Write the MULTIPLY function.
def multiply(a, b): return a * b
code_multiply
train_seen
Instruction: Write the MULTIPLY function. Answer: def multiply(a, b): return a * b <END>
If the current repo state is unknown, what do you ask for?
Ask for the missing evidence.
evidence_missing
train_regression
Instruction: If the current repo state is unknown, what do you ask for? Answer: Ask for the missing evidence. <END>
Is this code or prose: def add(a, b): return a + b
code
classify_code
train_seen
Instruction: Is this code or prose: def add(a, b): return a + b Answer: code <END>
Conversation: User: The name is Evan. User: What is the name?
Evan.
context_name
train_seen
Instruction: Conversation: User: The name is Evan. User: What is the name? Answer: Evan. <END>
Write multiply(a, b).
def multiply(a, b): return a * b
code_multiply
train_seen
Instruction: Write multiply(a, b). Answer: def multiply(a, b): return a * b <END>
Make a function called add that uses plus.
def add(a, b): return a + b
code_add
train_seen
Instruction: Make a function called add that uses plus. Answer: def add(a, b): return a + b <END>
Make a function called subtract that uses minus.
def subtract(a, b): return a - b
code_subtract
train_regression
Instruction: Make a function called subtract that uses minus. Answer: def subtract(a, b): return a - b <END>
If you cannot verify the project state, what is the right response?
Ask for the missing evidence.
evidence_missing
train_seen
Instruction: If you cannot verify the project state, what is the right response? Answer: Ask for the missing evidence. <END>
Sentiment of this text: This is broken.
negative
sentiment_negative
train_seen
Instruction: Sentiment of this text: This is broken. Answer: negative <END>
Write subtract(a, b).
def subtract(a, b): return a - b
code_subtract
train_seen
Instruction: Write subtract(a, b). Answer: def subtract(a, b): return a - b <END>
If the current repo state is unknown, what do you ask for?
Ask for the missing evidence.
evidence_missing
train_regression
Instruction: If the current repo state is unknown, what do you ask for? Answer: Ask for the missing evidence. <END>
Before claiming root cause without proof, what should you do?
Ask for the missing evidence.
evidence_missing
train_seen
Instruction: Before claiming root cause without proof, what should you do? Answer: Ask for the missing evidence. <END>
Write the ADD function.
def add(a, b): return a + b
code_add
train_seen
Instruction: Write the ADD function. Answer: def add(a, b): return a + b <END>
Remember inside this prompt: password is blue. Question: What is the password?
blue.
context_password
train_seen
Instruction: Remember inside this prompt: password is blue. Question: What is the password? Answer: blue. <END>
What should happen before touching code?
Inspect the current files first.
inspect_first
train_seen
Instruction: What should happen before touching code? Answer: Inspect the current files first. <END>
What should you do before editing a project?
Inspect the current files first.
inspect_first
train_seen
Instruction: What should you do before editing a project? Answer: Inspect the current files first. <END>
End of preview. Expand in Data Studio

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Check out the documentation for more information.

TT639B Targeted Assistant Ladder v1

Goal: Repair TT639 dense failure groups using the actual TT639 report.

This is not a broad chatbot/general-knowledge claim. It targets:

  • evidence-missing / no blind patch behavior
  • context-name prompt binding
  • add/subtract wording variants
  • unknown favorite movie behavior

Gate: TT639B only starts after TT638D dense + dyadic/Mercy proof and TT639 dense failure evidence.

Next gate: Only run TT639B dyadic/Mercy compare if dense seen + regression + rule + heldout all pass.

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